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Found 2 papers, 1 papers with code
A Kernel Theory of Modern Data Augmentation
Data augmentation, a technique in which a training set is expanded with class-preserving transformations, is ubiquitous in modern machine learning pipelines.
Learning to Compose Domain-Specific Transformations for Data Augmentation
Data augmentation is a ubiquitous technique for increasing the size of labeled training sets by leveraging task-specific data transformations that preserve class labels.
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